10 citations · 11 across the 4 of their papers we have counts for
5 papers
CS1QA: A Dataset for Assisting Code-based Question Answering in an Introductory Programming Course
Changyoon Lee, Yeon Seonwoo, Alice Oh
We introduce CS1QA, a dataset for code-based question answering in the programming education domain. CS1QA consists of 9,237 question-answer pairs gathered from chat logs in an int…
Two-Step Question Retrieval for Open-Domain QA
Yeon Seonwoo, Juhee Son, Jiho Jin +4
The retriever-reader pipeline has shown promising performance in open-domain QA but suffers from a very slow inference speed. Recently proposed question retrieval models tackle thi…
Weakly Supervised Pre-Training for Multi-Hop Retriever
Yeon Seonwoo, Sang-Woo Lee, Ji-Hoon Kim +2
In multi-hop QA, answering complex questions entails iterative document retrieval for finding the missing entity of the question. The main steps of this process are sub-question de…
Context-Aware Answer Extraction in Question Answering
Yeon Seonwoo, Ji-Hoon Kim, Jung-Woo Ha +1
Extractive QA models have shown very promising performance in predicting the correct answer to a question for a given passage. However, they sometimes result in predicting the corr…
TED Talk Recommender Using Speech Transcripts
Jaehoon Oh, Injung Lee, Yeon Seonwoo +3
Nowadays, online video platforms mostly recommend related videos by analyzing user-driven data such as viewing patterns, rather than the content of the videos. However, content is…